def error(coords_list):
seeds = fixed_seeds.copy()
print(f'coordinate list : {coords_list}')
print(f'seeds : {seeds}')
for index in range(len(coords_list) // 2):
coordinate = (int(coords_list[2 * index]),
int(coords_list[2 * index + 1]))
seeds.update({coordinate: colour})
segmentation = Segmentation(image_array,
beta,
seeds,
image_name,
reference_path=target_segmentation_path)
segmentation.solve()
segmentation.build_segmentation_image()
return segmentation.compute_error()
for key, value in initial_seeds.items() if value == 'red'
}
initial_coords = list(initial_variable_seeds.keys())
print(f'initial coords = {initial_coords}')
optimal_coords = optimize.minimize(error,
initial_coords,
method='nelder-mead',
constraints=cons,
options={
'xtol': 1e-3,
'disp': True
})
optimal_seeds = fixed_seeds
for index in range(len(optimal_coords) // 2):
coordinate = (int(optimal_coords[2 * index]),
int(optimal_coords[2 * index + 1]))
optimal_seeds.update({coordinate: colour})
# optimal segmentation
segmentation = Segmentation(image_array,
beta,
optimal_seeds,
image_name,
reference_path=target_segmentation_path)
segmentation.solve()
segmentation.build_segmentation_image()
segmentation.compute_error()
segmentation.contours_to_png()
std_list = np.linspace(0, 0.02, size)
betas_list = np.linspace(0, 5000, size)
error_values = []
with open(seeds_file_path, 'rb') as seeds_file:
seeds = pickle.load(seeds_file)
for noise_std in std_list:
segmentation = Segmentation(image_array, 1, seeds, image_name)
segmentation.add_noise(0, noise_std)
segmentation.set_reference_segmentation(target_segmentation_path)
for beta in betas_list:
print(f'index = {index}, beta = {beta}, std = {noise_std}')
segmentation.beta = beta
segmentation.solve()
segmentation.build_segmentation_image()
error_values.append(segmentation.compute_error())
index += 1
X, Y = np.meshgrid(betas_list, std_list)
triang = mtri.Triangulation(np.reshape(
X, [size*size]), np.reshape(Y, [size*size]))
fig = plt.figure()
ax = plt.axes(projection='3d')
ax.set_xlabel(r'$\beta$')
ax.set_ylabel('noise')
ax.set_zlabel('error')
ax.set_zlim3d(0, 0.085)
ax.set_zticks([0.1])
ax.set_xticks([0, 5000])
ax.set_yticks([0, 0.02])
